Automated Non-Invasive Coronary Artery Disease detection using Artificial Intelligence (ANICAD)

Year of award: 2021

Grantholders

  • Prof Sebastien Ourselin

    King's College London, United Kingdom

  • Prof Reza Razavi

    King's College London, United Kingdom

  • Prof Amedeo Chiribiri

    King's College London, United Kingdom

  • Dr Cian Scannell

    King's College London, United Kingdom

  • Prof Alistair Young

    King's College London, United Kingdom

Project summary

Coronary artery disease (CAD) is the most common cause of death in the UK. Modern medical imaging scans, such as cardiac magnetic resonance imaging (CMR), allow an accurate, non-invasive and radiation-free diagnosis of CAD and the early identification of patients that would benefit from available treatments, before complications such as heart attack and heart failure develop. There are not enough doctors in the UK trained to accurately interpret these scans, and this results in an underutilisation of CMR, also with significant regional variations. We will bridge this gap by creating computer programs based on artificial intelligence that, acting as expert digital doctors, will facilitate the interpretation of the scans and guide the clinical team in the management of patients with suspected CAD. This technology will enable advanced imaging to be rolled out in any hospital equipped with a suitable magnetic resonance scanner, regardless of the presence on-site of trained doctors.